Chemistry Institute, University of Campinas (UNICAMP), POB 6154, Campinas, SP, 13083-970, Brazil.
J Comput Aided Mol Des. 2012 Sep;26(9):1055-65. doi: 10.1007/s10822-012-9598-2. Epub 2012 Sep 13.
A new Receptor-Dependent LQTA-QSAR approach, RD-LQTA-QSAR, is proposed as a new 4D-QSAR method. It is an evolution of receptor independent LQTA-QSAR. This approach uses the free GROMACS package to carry out molecular dynamics simulations and generates a conformational ensemble profile for each compound. Such an ensemble is used to build molecular interaction field-based QSAR models, as in CoMFA. To show the potential of this methodology, a set of 38 phenothiazine derivatives that are specific competitive T. cruzi trypanothione reductase inhibitors, was chosen. Using a combination of molecular docking and molecular dynamics simulations, the binding mode of the phenotiazine derivatives was evaluated in a simulated induced fit approach. The ligands alignments were performed using both ligand and binding site atoms, enabling unbiased alignment. The models obtained were extensively validated by leave-N-out cross-validation and y-randomization techniques to test for their robustness and absence of chance correlation. The final model presented Q(2) LOO of 0.87 and R² of 0.92 and a suitable external prediction of [Formula: see text]= 0.78. The adapted binding site obtained is useful to perform virtual screening and ligand structure-based design and the descriptors in the final model can aid in the design new inhibitors.
提出了一种新的受体依赖的 LQTA-QSAR 方法，称为 RD-LQTA-QSAR，作为一种新的 4D-QSAR 方法。它是受体独立的 LQTA-QSAR 的发展。该方法使用免费的 GROMACS 软件包进行分子动力学模拟，并为每个化合物生成构象集合分布。这种集合用于构建基于分子相互作用场的 QSAR 模型，就像 CoMFA 一样。为了展示该方法的潜力，选择了一组 38 种苯并噻嗪衍生物，它们是特异性竞争 T. cruzi 三肽还原酶抑制剂。通过分子对接和分子动力学模拟的结合，在模拟诱导拟合方法中评估了苯并噻嗪衍生物的结合模式。使用配体和结合位点原子对配体进行了对齐，实现了无偏对齐。通过留一法交叉验证和 y-随机化技术对获得的模型进行了广泛验证，以测试其稳健性和无机会相关性。最终模型的 Q²LOO 为 0.87，R²为 0.92，外部预测[公式：见文本]为 0.78。获得的适应性结合位点可用于进行虚拟筛选和基于配体结构的设计，最终模型中的描述符可用于设计新的抑制剂。
